Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Digital signal processing (DSP) is a technical field concerned with the representation of continuous analog signals by a sequence of discrete numbers or symbols and the processing of such discrete sequences. DSP applications process signals to measure, filter, manipulate, and/or compress continuous analog signals. A step in a DSP application may be to convert a continuous analog signal to a sequence of discrete digital samples. Such digital sampling may be performed by an analog-to-digital converter (ADC). Further, the output signal for a DSP application may be another continuous analog output signal, which may use a digital-to-analog converter (DAC) to transform a sequence of digital samples into the continuous analog signal. DSP applications include audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for communications, control of systems, biomedical signal processing, seismic data processing, etc.
DSP algorithms may be performed by standard computers, computing devices or microprocessors, by specialized processors called digital signal processors (DSPs), or on specialized hardware such as application-specific integrated circuit (ASICs). In addition, digital signal processing may be performed on more powerful general purpose microprocessors, field-programmable gate arrays (FPGAs), digital signal controllers (mostly for industrial application such as motor control), and stream processors, among others.
Oftentimes, a digital signal processing system incorporates a transform from a discrete time-domain signal to a discrete frequency-domain signal. A discrete time-domain signal is a digital signal that has separate samples that have been sampled with respect to time. With such a signal, each sample corresponds to a different point in time. The value of each sample corresponds to the magnitude of the sampled signal at a given time. The discrete time-domain signal may be sampled at uniform time samples or at non-uniform time samples. For example, an incoming radio frequency wireless signal may be sampled at 1 microsecond intervals to create a discrete time-domain digital signal.
Once the radio frequency has been sampled in the time domain, creating a discrete time-domain signal, it is possible to use a mathematical transform to convert a time domain sample into a frequency-domain sample. The Fourier Transform is an operation that can be used to transform time-domain signals into frequency-domain signals. For example, in an OFDM communication system, data is received and sampled in the time domain. These discrete time-domain samples are converted to frequency-domain samples through the Fourier transform operation. The frequency bins associated with the frequency-domain signal contain data.